We introduce an inexact Gauss–Newton trust-region method for solving bound-constrained nonlinear least-squares problems where, at each iteration, a trust-region subproblem is approximately solved by the Conjugate Gradient method. Provided a suitable control on the accuracy to which we attempt to solve the subproblems, we prove that the method has global and asymptotic fast convergence properties. Some numerical illustration is also presented
A class of trust region based algorithms is presented for the solution of nonlinear optimization pro...
In this paper, we consider the problem of solving nonlinear equations F (x) = 0, where F (x) from ! ...
This work presents a global convergence theory for a broad class of trust-region algorithms for the ...
We introduce an inexact Gauss\u2013Newton trust-region method for solving bound-constrained nonlinea...
Abstract. The Matlab implementation of a trust-region Gauss-Newton method for bound-constrained nonl...
AbstractThis paper presents a new method with trust region technique for solving the nonlinear least...
We present a local convergence analysis of inexact Gauss-Newton-like method (IGNLM) for solving nonl...
The Matlab implementation of a trust-region Gauss-Newton method for bound-constrained nonlinear leas...
The minimization of a quadratic function within an ellipsoidal trust region is an important subprobl...
The minimization of a quadratic function within an ellipsoidal trust region is an important subprobl...
In this paper, two new trust-region algorithms for the numerical solution of systems of nonlinear eq...
Two trust-region methods for systems of mixed nonlinear equalities, general inequalities and simple ...
Abstract. We consider methods for large-scale unconstrained minimization based on finding an approxi...
Trust-region quadratic methods for bound-constrained nonlinear least-squares and nonlinear feasibili...
An iterative method for solving bound-constrained underdetermined nonlinear systems is presented. Th...
A class of trust region based algorithms is presented for the solution of nonlinear optimization pro...
In this paper, we consider the problem of solving nonlinear equations F (x) = 0, where F (x) from ! ...
This work presents a global convergence theory for a broad class of trust-region algorithms for the ...
We introduce an inexact Gauss\u2013Newton trust-region method for solving bound-constrained nonlinea...
Abstract. The Matlab implementation of a trust-region Gauss-Newton method for bound-constrained nonl...
AbstractThis paper presents a new method with trust region technique for solving the nonlinear least...
We present a local convergence analysis of inexact Gauss-Newton-like method (IGNLM) for solving nonl...
The Matlab implementation of a trust-region Gauss-Newton method for bound-constrained nonlinear leas...
The minimization of a quadratic function within an ellipsoidal trust region is an important subprobl...
The minimization of a quadratic function within an ellipsoidal trust region is an important subprobl...
In this paper, two new trust-region algorithms for the numerical solution of systems of nonlinear eq...
Two trust-region methods for systems of mixed nonlinear equalities, general inequalities and simple ...
Abstract. We consider methods for large-scale unconstrained minimization based on finding an approxi...
Trust-region quadratic methods for bound-constrained nonlinear least-squares and nonlinear feasibili...
An iterative method for solving bound-constrained underdetermined nonlinear systems is presented. Th...
A class of trust region based algorithms is presented for the solution of nonlinear optimization pro...
In this paper, we consider the problem of solving nonlinear equations F (x) = 0, where F (x) from ! ...
This work presents a global convergence theory for a broad class of trust-region algorithms for the ...